Aircraft Detection¶

Get Pleiades imagery for the given airports
Execute tiling and aircraft detection blocks via parallel jobs
Visualize the results
The example costs around 1700 UP42 credits

Setup¶

Import required libraries

In [2]:

import up42
import geopandas as gpd
import rasterio
from rasterio.plot import show
import matplotlib.pyplot as plt
from shapely.geometry import box

Configure areas of interest

In [3]:

aoi_txl = {"type":"FeatureCollection","features":[{"type":"Feature","properties":{},
                "geometry":{"type":"Polygon","coordinates":[[[13.286740779876709,52.5509016976356],
                                                             [13.300495147705078,52.5509016976356],
                                                             [13.300495147705078,52.556890079685594],
                                                             [13.286740779876709,52.556890079685594],
                                                             [13.286740779876709,52.5509016976356]]]}}]}
aoi_muc = {"type":"FeatureCollection","features":[{"type":"Feature","properties":{},
                "geometry":{"type":"Polygon","coordinates":[[[11.789016723632812,48.348577346994944],
                                                             [11.809401512145996,48.348577346994944],
                                                             [11.809401512145996,48.360155725059116],
                                                             [11.789016723632812,48.360155725059116],
                                                             [11.789016723632812,48.348577346994944]]]}}]}


aois = [{'title': 'TXL', 'geometry': aoi_txl},
        {'title': 'MUC', 'geometry': aoi_muc}]

Authenticate with UP42

In [4]:

#up42.authenticate(project_id="123", project_api_key="456")
up42.authenticate(cfg_file="config.json")
up42.settings(log=False)

2020-11-11 22:59:10,921 - Got credentials from config file.
2020-11-11 22:59:11,197 - Authentication with UP42 successful!
2020-11-11 22:59:11,198 - Logging disabled - use up42.settings(log=True) to reactivate.

Catalog Search¶

Search cloudfree Pleiades image for the two aois and visualise the quicklooks.

In [5]:

catalog = up42.initialize_catalog()


for aoi in aois:
    print("\n---------" + aoi["title"] + "---------\n")
    search_paramaters = catalog.construct_parameters(geometry=aoi['geometry'], 
                                                     start_date="2020-04-01",
                                                     end_date="2020-04-30",
                                                     sensors=["pleiades"],
                                                     max_cloudcover=10,
                                                     sortby="acquisitionDate",
                                                     ascending=False,
                                                     limit=3)
    search_results = catalog.search(search_paramaters)
    
    # Download & Visualise quicklooks
    catalog.download_quicklooks(image_ids=search_results.id.to_list(), sensor="pleiades")
    display(search_results.head())
    catalog.plot_quicklooks(figsize=(18,5), titles=search_results.scene_id.to_list())

    # Select least cloud scene for further workflow
    aoi["scene_id"] = search_results.scene_id.to_list()[0]

---------TXL---------

100%|██████████| 3/3 [00:01<00:00,  1.73it/s]

	geometry	id	acquisitionDate	constellation	providerName	blockNames	cloudCoverage	up42:usageType	providerProperties	scene_id
0	POLYGON ((13.20640 52.58098, 13.20616 52.45458...	c5497393-8f8d-4367-9527-c39344e220fe	2020-04-28T10:31:35Z	PHR	oneatlas	[oneatlas-pleiades-fullscene, oneatlas-pleiade...	2.31	[DATA, ANALYTICS]	{'commercialReference': 'SO20025725', 'acquisi...	DS_PHR1B_202004281031350_FR1_PX_E013N52_0513_0...
1	POLYGON ((13.21800 52.58082, 13.21860 52.45684...	07e5eaba-7830-4aee-8c27-6b69fa1da89f	2020-04-23T10:19:52Z	PHR	oneatlas	[oneatlas-pleiades-fullscene, oneatlas-pleiade...	0.00	[DATA, ANALYTICS]	{'commercialReference': 'SO20022129', 'acquisi...	DS_PHR1B_202004231019525_FR1_PX_E013N52_0513_0...
2	POLYGON ((13.20760 52.58274, 13.20828 52.45502...	11616f18-4002-44fc-bfeb-571c6657ccf4	2020-04-17T10:16:45Z	PHR	oneatlas	[oneatlas-pleiades-fullscene, oneatlas-pleiade...	0.40	[DATA, ANALYTICS]	{'commercialReference': 'SO20017653', 'acquisi...	DS_PHR1A_202004171016453_FR1_PX_E013N52_0513_0...

---------MUC---------

100%|██████████| 3/3 [00:01<00:00,  2.09it/s]

	geometry	id	acquisitionDate	constellation	providerName	blockNames	cloudCoverage	up42:usageType	providerProperties	scene_id
0	POLYGON ((11.62946 48.39067, 11.62967 48.29748...	0e324d95-47df-48f7-9a49-76a9aaa93362	2020-04-16T10:25:42Z	PHR	oneatlas	[oneatlas-pleiades-fullscene, oneatlas-pleiade...	0.00	[DATA, ANALYTICS]	{'commercialReference': 'SO20017376', 'acquisi...	DS_PHR1B_202004161025425_FR1_PX_E011N48_1009_0...
1	POLYGON ((11.63674 48.40241, 11.63713 48.31271...	b9d55cf6-6a6b-4a41-9998-0fc69e1d4515	2020-04-11T10:14:13Z	PHR	oneatlas	[oneatlas-pleiades-fullscene, oneatlas-pleiade...	0.08	[DATA, ANALYTICS]	{'commercialReference': 'SO20016407', 'acquisi...	DS_PHR1B_202004111014133_FR1_PX_E011N48_1009_0...
2	POLYGON ((11.64703 48.39837, 11.64731 48.30483...	6573a62a-819b-4d2e-b27d-8bbd904e6549	2020-04-10T10:20:58Z	PHR	oneatlas	[oneatlas-pleiades-fullscene, oneatlas-pleiade...	0.05	[DATA, ANALYTICS]	{'commercialReference': 'SO20015930', 'acquisi...	DS_PHR1A_202004101020584_FR1_PX_E011N48_1009_0...

In [10]:

# Optional: Select ideal scenes manually
aois[0]["scene_id"] = "DS_PHR1B_202004281031350_FR1_PX_E013N52_0513_01239"
aois[1]["scene_id"] = "DS_PHR1B_202004161025425_FR1_PX_E011N48_1009_00822"

Download selected Pleiades images for aois¶

In [14]:

up42.settings(log=True)
project = up42.initialize_project()

# Increase the parallel job limit for the project.
#project.update_project_settings(max_concurrent_jobs=10)

2020-11-11 18:13:41,729 - Logging enabled (default) - use up42.settings(log=False) to disable.
2020-11-11 18:13:42,369 - Initialized Project(name: Aircraft Detection TXL-MUC, project_id: 0a448563-a2e6-41f3-abf6-737d036309ee, description: , createdAt: 2020-11-11T16:45:02.388745Z)

Create or update a workflow for the aircraft detection

In [15]:

workflow = project.create_workflow("Aircraft detection", use_existing=True)

2020-11-11 18:13:57,529 - Getting existing workflows in project ...
2020-11-11 18:13:57,836 - Got 0 workflows for project 0a448563-a2e6-41f3-abf6-737d036309ee.
0it [00:00, ?it/s]
2020-11-11 18:13:58,168 - Created new workflow: ea37cc26-396b-4d67-b22e-855786bd23af

Add or update workflows tasks

In [23]:

#up42.get_blocks(basic=True)
input_tasks= ['oneatlas-pleiades-aoiclipped', 'tiling', 'orbital_pleiades_aircraft']
workflow.add_workflow_tasks(input_tasks=input_tasks)
workflow

2020-11-11 18:29:12,006 - Added tasks to workflow: [{'name': 'oneatlas-pleiades-aoiclipped:1', 'parentName': None, 'blockId': '18d09f1a-3197-4c27-a15a-54d099c31435'}, {'name': 'tiling:1', 'parentName': 'oneatlas-pleiades-aoiclipped:1', 'blockId': '3e146dd6-2b67-4d6e-a422-bb3d973e32ff'}, {'name': 'orbital_pleiades_aircraft:1', 'parentName': 'tiling:1', 'blockId': '4f2f3438-d31b-4872-ab15-ce50160dd70e'}]

Out[23]:

Workflow(name: Aircraft detection, workflow_id: ea37cc26-396b-4d67-b22e-855786bd23af, description: , createdAt: 2020-11-11T17:13:58.145399Z, project_name: Aircraft detection, workflow_tasks: {'oneatlas-pleiades-aoiclipped:1': '2.1.1', 'tiling:1': '2.2.3', 'orbital_pleiades_aircraft:1': '1.1.2-public'}

Run jobs in parallel¶

Construct workflow input parameters & run jobs

In [24]:

input_parameters_list = []

for aoi in aois:
    input_parameters = workflow.construct_parameters(geometry=aoi['geometry'], 
                                                     geometry_operation="bbox", 
                                                     scene_ids=[aoi["scene_id"]])
    input_parameters['tiling:1']['tile_width']  = 1024
    input_parameters['tiling:1']['tile_height'] = 1024
    input_parameters_list.append(input_parameters)

input_parameters_list

Out[24]:

[{'oneatlas-pleiades-aoiclipped:1': {'limit': 1,
   'zoom_level': 18,
   'max_cloud_cover': 100,
   'panchromatic_band': False,
   'ids': ['DS_PHR1B_202004281031350_FR1_PX_E013N52_0513_01239'],
   'bbox': [13.286740779876709,
    52.5509016976356,
    13.300495147705078,
    52.556890079685594]},
  'tiling:1': {'tile_width': 1024,
   'tile_height': 1024,
   'match_extents': False,
   'output_prefix': '',
   'augmentation_factor': 1,
   'discard_empty_tiles': True},
  'orbital_pleiades_aircraft:1': {}},
 {'oneatlas-pleiades-aoiclipped:1': {'limit': 1,
   'zoom_level': 18,
   'max_cloud_cover': 100,
   'panchromatic_band': False,
   'ids': ['DS_PHR1B_202004161025425_FR1_PX_E011N48_1009_00822'],
   'bbox': [11.789016723632812,
    48.348577346994944,
    11.809401512145996,
    48.360155725059116]},
  'tiling:1': {'tile_width': 1024,
   'tile_height': 1024,
   'match_extents': False,
   'output_prefix': '',
   'augmentation_factor': 1,
   'discard_empty_tiles': True},
  'orbital_pleiades_aircraft:1': {}}]

In [25]:

jobs = workflow.run_jobs_parallel(input_parameters_list=input_parameters_list)

2020-11-11 18:30:25,609 - Selected input_parameters: {'oneatlas-pleiades-aoiclipped:1': {'limit': 1, 'zoom_level': 18, 'max_cloud_cover': 100, 'panchromatic_band': False, 'ids': ['DS_PHR1B_202004281031350_FR1_PX_E013N52_0513_01239'], 'bbox': [13.286740779876709, 52.5509016976356, 13.300495147705078, 52.556890079685594]}, 'tiling:1': {'tile_width': 1024, 'tile_height': 1024, 'match_extents': False, 'output_prefix': '', 'augmentation_factor': 1, 'discard_empty_tiles': True}, 'orbital_pleiades_aircraft:1': {}}.
2020-11-11 18:30:29,248 - Created and running new job: 1e7f5b2d-9a9c-4155-85ea-58b36a1e5d59
2020-11-11 18:30:29,575 - Selected input_parameters: {'oneatlas-pleiades-aoiclipped:1': {'limit': 1, 'zoom_level': 18, 'max_cloud_cover': 100, 'panchromatic_band': False, 'ids': ['DS_PHR1B_202004161025425_FR1_PX_E011N48_1009_00822'], 'bbox': [11.789016723632812, 48.348577346994944, 11.809401512145996, 48.360155725059116]}, 'tiling:1': {'tile_width': 1024, 'tile_height': 1024, 'match_extents': False, 'output_prefix': '', 'augmentation_factor': 1, 'discard_empty_tiles': True}, 'orbital_pleiades_aircraft:1': {}}.
2020-11-11 18:30:32,473 - Created and running new job: 8f7801de-d00a-4f59-8e4e-a61750148b29
2020-11-11 18:30:32,810 - Tracking job status continuously, reporting every 20 seconds...
2020-11-11 18:30:56,512 - Job is RUNNING! - 1e7f5b2d-9a9c-4155-85ea-58b36a1e5d59
2020-11-11 18:31:20,901 - Job is RUNNING! - 1e7f5b2d-9a9c-4155-85ea-58b36a1e5d59
2020-11-11 18:31:44,278 - Job is RUNNING! - 1e7f5b2d-9a9c-4155-85ea-58b36a1e5d59
2020-11-11 18:32:05,658 - Job is RUNNING! - 1e7f5b2d-9a9c-4155-85ea-58b36a1e5d59
2020-11-11 18:32:28,017 - Job is RUNNING! - 1e7f5b2d-9a9c-4155-85ea-58b36a1e5d59
2020-11-11 18:32:51,364 - Job is RUNNING! - 1e7f5b2d-9a9c-4155-85ea-58b36a1e5d59
2020-11-11 18:33:14,892 - Job finished successfully! - 1e7f5b2d-9a9c-4155-85ea-58b36a1e5d59
2020-11-11 18:33:19,893 - Tracking job status continuously, reporting every 20 seconds...
2020-11-11 18:33:41,591 - Job is RUNNING! - 8f7801de-d00a-4f59-8e4e-a61750148b29
2020-11-11 18:33:52,284 - Job finished successfully! - 8f7801de-d00a-4f59-8e4e-a61750148b29

Download & Visualise results¶

In [43]:

data_results_paths, detection_results = [], []
for job in jobs:
    data_task, _, detection_task = job.get_jobtasks()
    data_paths = data_task.download_results()
    data_results_paths.append([p for p in data_paths if p.endswith(".tif")])
    detection_results.append(detection_task.get_results_json())

2020-11-11 18:40:54,657 - Getting job tasks: 1e7f5b2d-9a9c-4155-85ea-58b36a1e5d59
2020-11-11 18:40:56,159 - Downloading results of jobtask 2e5bc39f-6033-4c5b-9087-2231d8586ca4
2020-11-11 18:40:56,161 - Download directory: /Users/christoph.rieke/repos/up42-py/examples/project_0a448563-a2e6-41f3-abf6-737d036309ee/job_1e7f5b2d-9a9c-4155-85ea-58b36a1e5d59/jobtask_2e5bc39f-6033-4c5b-9087-2231d8586ca4
16346it [00:00, 419474.03it/s]
2020-11-11 18:40:58,315 - Download successful of 3 files to output_directory '/Users/christoph.rieke/repos/up42-py/examples/project_0a448563-a2e6-41f3-abf6-737d036309ee/job_1e7f5b2d-9a9c-4155-85ea-58b36a1e5d59/jobtask_2e5bc39f-6033-4c5b-9087-2231d8586ca4': ['usage.json', 'data.json', '46ebeb50-7109-4d0e-bc4c-377df12b5d04.tif']
2020-11-11 18:40:58,745 - Retrieved 17 features.
2020-11-11 18:40:58,746 - Getting job tasks: 8f7801de-d00a-4f59-8e4e-a61750148b29
2020-11-11 18:41:00,169 - Downloading results of jobtask 5cd8d78c-ba26-4f3f-8fbe-57a02ac1f12f
2020-11-11 18:41:00,170 - Download directory: /Users/christoph.rieke/repos/up42-py/examples/project_0a448563-a2e6-41f3-abf6-737d036309ee/job_8f7801de-d00a-4f59-8e4e-a61750148b29/jobtask_5cd8d78c-ba26-4f3f-8fbe-57a02ac1f12f
41688it [00:00, 467632.89it/s]
2020-11-11 18:41:04,617 - Download successful of 3 files to output_directory '/Users/christoph.rieke/repos/up42-py/examples/project_0a448563-a2e6-41f3-abf6-737d036309ee/job_8f7801de-d00a-4f59-8e4e-a61750148b29/jobtask_5cd8d78c-ba26-4f3f-8fbe-57a02ac1f12f': ['6e8adf74-021f-4ef8-b97a-3dbdce2e5c2b.tif', 'usage.json', 'data.json']
2020-11-11 18:41:05,038 - Retrieved 76 features.

In [48]:

for i, (paths, detection) in enumerate(zip(data_results_paths, detection_results)):
    with rasterio.open(paths[0]) as src:
        fig, ax = plt.subplots(figsize=(18, 18))

        planes = gpd.GeoDataFrame.from_features(detection, crs={'init': "EPSG:4326"})
        planes = planes.to_crs(epsg=3857)
        planes.geometry = planes.geometry.buffer(0.0001)
        planes.geometry = planes.geometry.apply(lambda geo:box(*geo.bounds))

        show(src.read(), transform=src.transform, ax=ax, title=f"{aois[i]['title']}: {planes.shape[0]} planes detected")
    
        planes.plot(ax=ax, facecolor=(0,0,0,0), edgecolor='red', linewidth=2)
        
        plt.show()

In [ ]: